Abstract: The purpose of this study is to evaluate the monetary worthiness of investment and the usefulness of risk estimation as a tool employed by a production section of an electronic factory. This study employed the case study of accidents occurring in production areas. Data is collected from interviews with six production of safety coordinators and collect the information from the relevant section. The study will present the ratio of benefits compared with the operation costs for investment. The result showed that it is worthwhile for investment with the safety measures. In addition, the organizations must be able to analyze the causes of accidents about the benefits of investing in protective working process. They also need to quickly provide the manual for the staff to learn how to protect themselves from accidents and how to use all of the safety equipment.
Abstract: Anaplasma organisms are obligatory intracellular bacteria belonging to the order Rickettsiales, family Anaplasmataceae. This disease is distributed around the globe and infected ticks are the most important vectors in anaplasmosis transmission. There is a little information about anaplasmosis in camels. This research investigated the blood films of 35 (20 male, 15 female) camels randomly selected from a flock of 150 camels. Samples were stained with Giemsa and Anaplasma sp. organisms were observed in six out of 35 (17.14 %) blood films. There were also some changes in Diff-Quick and morphology of leukocytes. No significant difference between male and female camels was observed (P>0.05). According to the results anaplasmosis is presented among camels in Iran.
Abstract: Firms are increasingly responding to social and environmental claims from society. Practices oriented to attend issues such as poverty, work equality, or renewable energy, are being implemented more frequently by firms to address impacts on sustainability. However, questions remain on how the responses of firms vary across industries and regions between the social and the economic objectives. Using concepts from organizational theory and social network theory, this paper aims to create a theoretical framework that explains the internal and external influences that make a firm establish its objective. The framework explains why firms might have a different objective orientation in terms of its economic and social prioritization.
Abstract: The biological function of an RNA molecule depends
on its structure. The objective of the alignment is finding the
homology between two or more RNA secondary structures. Knowing
the common functionalities between two RNA structures allows
a better understanding and a discovery of other relationships
between them. Besides, identifying non-coding RNAs -that is not
translated into a protein- is a popular application in which RNA
structural alignment is the first step A few methods for RNA
structure-to-structure alignment have been developed. Most of these
methods are partial structure-to-structure, sequence-to-structure, or
structure-to-sequence alignment. Less attention is given in the
literature to the use of efficient RNA structure representation and the
structure-to-structure alignment methods are lacking. In this paper,
we introduce an O(N2) Component-based Pairwise RNA Structure
Alignment (CompPSA) algorithm, where structures are given as
a component-based representation and where N is the maximum
number of components in the two structures. The proposed algorithm
compares the two RNA secondary structures based on their weighted
component features rather than on their base-pair details. Extensive
experiments are conducted illustrating the efficiency of the CompPSA
algorithm when compared to other approaches and on different real
and simulated datasets. The CompPSA algorithm shows an accurate
similarity measure between components. The algorithm gives the
flexibility for the user to align the two RNA structures based on
their weighted features (position, full length, and/or stem length).
Moreover, the algorithm proves scalability and efficiency in time and
memory performance.
Abstract: This article is an extension of previous research presenting the relevant factors related to environmental perceptions, residential community, and the design of a healing environment, which have effects on the well-being and requirements of Thai elderly. Research methodology began with observations and interviews in three case studies in terms of the management processes and environment design of similar existing projects in Thailand. The interview results were taken to summarize with related theories and literature. A questionnaire survey was designed for data collection to confirm the factors of requirements in a residential community intended for the Thai elderly. A structural equation model (SEM) was formulated to explain the cause-effect factors for the requirements of a residential community for Thai elderly. The research revealed that the requirements of a residential community for Thai elderly were classified into three groups when utilizing a technique for exploratory factor analysis. The factors were comprised of (1) requirements for general facilities and activities, (2) requirements for facilities related to health and security, and (3) requirements for facilities related to physical exercise in the residential community. The results from the SEM showed the background of elderly people had a direct effect on their requirements for a residential community from various aspects. The results should lead to the formulation of policies for design and management of residential communities for the elderly in order to enhance quality of life as well as both the physical and mental health of the Thai elderly.
Abstract: Determination of 90Sr in environmental samples has been widely developed with several radioanlytical methods and radiation measurement techniques since 90Sr is one of the most hazardous radionuclides produced from nuclear reactors. Liquid extraction technique using di-(2-ethylhexyl) phosphoric acid (HDEHP) to separate and purify 90Y and Cherenkov counting using liquid scintillation counter to determine 90Y in secular equilibrium to 90Sr was developed and performed at our institute, the Office of Atoms for Peace. The approach is inexpensive, non-laborious, and fast to analyse 90Sr in environmental samples. To validate our analytical performance for the accurate and precise criteria, determination of 90Sr using the IAEA-TEL-2016-04 ALMERA proficiency test samples were performed for statistical evaluation. The experiment used two spiked tap water samples and one naturally contaminated spruce needles sample from Austria collected shortly after the Chernobyl accident. Results showed that all three analyses were successfully passed in terms of both accuracy and precision criteria, obtaining “Accepted” statuses. The two water samples obtained the measured results of 15.54 Bq/kg and 19.76 Bq/kg, which had relative bias 5.68% and -3.63% for the Maximum Acceptable Relative Bias (MARB) 15% and 20%, respectively. And the spruce needles sample obtained the measured results of 21.04 Bq/kg, which had relative bias 23.78% for the MARB 30%. These results confirm our analytical performance of 90Sr determination in water and spruce needles samples using the same developed method.
Abstract: In this paper, we present an evolving knowledge
extraction system named AKEOS (Automatic Knowledge Extraction
from Online Sources). AKEOS consists of two modules, including
a one-time learning module and an evolving learning module.
The one-time learning module takes in user input query, and
automatically harvests knowledge from online unstructured resources
in an unsupervised way. The output of the one-time learning is a
structured vector representing the harvested knowledge. The evolving
learning module automatically schedules and performs repeated
one-time learning to extract the newest information and track the
development of an event. In addition, the evolving learning module
summarizes the knowledge learned at different time points to produce
a final knowledge vector about the event. With the evolving learning,
we are able to visualize the key information of the event, discover
the trends, and track the development of an event.
Abstract: Distillery wastewater in the form of spent wash is a complex and strong industrial effluent, with high load of organic pollutants that may deplete dissolved oxygen on being discharged into aquatic systems and contaminate groundwater by leaching of pollutants, while untreated spent wash disposed on land acidifies the soil. Stringent legislative measures have therefore been framed in different countries for discharge standards of distillery effluent. Utilising the organic pollutants present in various types of wastes as food by mixed microbial populations is emerging as an eco-friendly approach in the recent years, in which complex organic matter is converted into simpler forms, and simultaneously useful gases are produced as renewable and clean energy sources. In the present study, wastewater from a rice bran based distillery has been used as the substrate in a dark fermenter, and native microbial consortium from the digester sludge has been used as the inoculum to treat the wastewater and produce hydrogen. After optimising the operational conditions in batch reactors, sequential batch mode and continuous flow stirred tank reactors were used to study the best operational conditions for enhanced and sustained hydrogen production and removal of pollutants. Since the rate of hydrogen production by the microbial consortium during dark fermentation is influenced by concentration of organic matter, pH and temperature, these operational conditions were optimised in batch mode studies. Maximum hydrogen production rate (347.87ml/L/d) was attained in 32h dark fermentation while a good proportion of COD also got removed from the wastewater. Slightly acidic initial pH seemed to favor biohydrogen production. In continuous stirred tank reactor, high H2 production from distillery wastewater was obtained from a relatively shorter substrate retention time (SRT) of 48h and a moderate organic loading rate (OLR) of 172 g/l/d COD.
Abstract: The eudaimonic perspective in philosophy and psychology suggests that a good life is closely related to developing oneself in order to contribute to the well-being and happiness of other people and of the world as a whole. Educational psychology can help to achieve this through the design and validation of educative models. Since 2004, the University of Concepcion and other Chilean universities apply an educative model to train socially responsible professionals, people that in the exercise of their profession contribute to generate equity for the development and assess the impacts of their decisions, opting for those that serve the common good. The main aim is to identify if a relationship exists between achieved learning, attitudes toward social responsibility, self-attribution of socially responsible behavior, value type, professional behavior observed and, participation in a specific model to train socially responsible (SR) professionals. The Achieved Learning and Attitudes Toward Social Responsibility Questionnaire, interview with employers and Values Questionnaire and Self-attribution of SR Behavior Questionnaire is applied to 394 students and graduates, divided into experimental and control groups (trained and not trained under the educative model), in order to identify the professional behavior of the graduates. The results show that students and graduates perceive cognitive, affective and behavioral learning, with significant differences in attitudes toward social responsibility and self-attribution of SR behavior, between experimental and control. There are also differences in employers' perceptions about the professional practice of those who were trained under the model and those who were not. It is concluded that the educative model has an impact on the learning of social responsibility and educates for a full life. It is also concluded that it is necessary to identify mediating variables of the model effect.
Abstract: Attempts to split the construct of emotional intelligence (EI) into separate components – ability to understand own and others’ emotions and ability to control own and others’ emotions may be meaningful more theoretically than practically. In real life, a personality encounters various emotional situations that require exhibition of complex EI to solve them. Emotional situation solution tests enable measurement of such undivided EI. The object of the present study is to determine sociodemographic and other factors that are important for emotional situation solutions. The study involved 1,430 participants from various regions of Lithuania. The age of participants varied from 17 years to 27 years. Emotional social and interpersonal situation scale EI-DARL-V2 was used. Each situation had two mandatory answering formats: The first format contained assignments associated with hypothetical theoretical knowledge of how the situation should be solved, while the second format included the question of how the participant would personally resolve the given situation in reality. A questionnaire that contained various sociodemographic data of subjects was also presented. Factors, statistically significant for emotional situation solution, have been determined: gender, family structure, the subject’s relation with his or her mother, mother’s occupation, subjectively assessed financial situation of the family, level of education of the subjects and his or her parents, academic achievement, etc. The best solvers of emotional situations are women with high academic achievements. According to their chosen study profile/acquired profession, they are related to the fields in social sciences and humanities. The worst solvers of emotional situations are men raised in foster homes. They are/were bad students and mostly choose blue-collar professions.
Abstract: This study aimed at developing an inverse heat transfer approach for predicting the time-varying freezing front and the temperature distribution of tumors during cryosurgery. Using a temperature probe pressed against the layer of tumor, the inverse approach is able to predict simultaneously the metabolic heat generation and the blood perfusion rate of the tumor. Once these parameters are predicted, the temperature-field and time-varying freezing fronts are determined with the direct model. The direct model rests on one-dimensional Pennes bioheat equation. The phase change problem is handled with the enthalpy method. The Levenberg-Marquardt Method (LMM) combined to the Broyden Method (BM) is used to solve the inverse model. The effect (a) of the thermal properties of the diseased tissues; (b) of the initial guesses for the unknown thermal properties; (c) of the data capture frequency; and (d) of the noise on the recorded temperatures is examined. It is shown that the proposed inverse approach remains accurate for all the cases investigated.
Abstract: Environmental legislation to protect North and Baltic Sea areas from harmful vessel-source emissions has received increased political attention in recent years. Legislative measures are expected to show positive effects on the health of the marine environment and society. At the same time, compliance might increase the costs to industry and have effects on freight rates and volumes shipped with potential negative repercussions on the environment. Building on an exploratory sequential mixed methods approach, this research project will study the economic effects of maritime environmental legislation in two phases. In Phase I, exploratory in-depth interviews were conducted with 12 experts from various stakeholder groups aiming at identifying variables influencing the relationship between environmental legislation, freight rates and volumes shipped. Influencing factors like compliance, enforcement and modal shift were identified and studied. Phase II will comprise of a quantitative study conducted with the aim of verifying the theory build in Phase I and quantifying economic effects of rules on shipping pollution. Research in this field might inform policy-makers about determinants of behaviour of ship operators in the face of the law and might further the development of a comprehensive legal system for marine environmental protection. At the present stage of research, first tentative results from the qualitative phase may be examined and open research questions to be addressed in the quantitative phase as well as possible research designs for phase II may be discussed. Input from other researchers will be highly valuable at this point.
Abstract: Separate collection system for recyclable wastes in the Helsinki region was ranked second best of European capitals. The collection system includes paper, cardboard, glass, metals and biowaste. Residual waste is collected and used in energy production. The collection system excluding paper is managed by the Helsinki Region Environmental Services HSY, a public organization owned by four municipalities (Helsinki, Espoo, Kauniainen and Vantaa). Paper collection is handled by the producer responsibility scheme. The efficiency of the collection system in the Helsinki region relies on a good coverage of door-to-door-collection. All properties with 10 or more dwelling units are required to source separate biowaste and cardboard. This covers about 75% of the population of the area. The obligation is extended to glass and metal in properties with 20 or more dwelling units. Other success factors include public awareness campaigns and a fee system that encourages recycling. As a result of waste management regulations for source separation of recyclables and biowaste, nearly 50 percent of recycling rate of household waste has been reached. For households and small and medium size enterprises, there is a sorting station fleet of five stations available. More than 50 percent of wastes received at sorting stations is utilized as material. The separate collection of plastic packaging in Finland will begin in 2016 within the producer responsibility scheme. HSY started supplementing the national bring point system with door-to-door-collection and pilot operations will begin in spring 2016. The result of plastic packages pilot project has been encouraging. Until the end of 2016, over 3500 apartment buildings have been joined the piloting, and more than 1800 tons of plastic packages have been collected separately. In the summer 2015 a novel partial flow digestion process combining digestion and tunnel composting was adopted for source separated household and commercial biowaste management. The product gas form digestion process is converted in to heat and electricity in piston engine and organic Rankine cycle process with very high overall efficiency. This paper describes the efficient collection system and discusses key success factors as well as main obstacles and lessons learned as well as the partial flow process for biowaste management.
Abstract: Inflation can be calculated from either the prices of consumer products or from salaries. This paper presents a logical exercise that shows it is easier to calculate inflation from salaries than from consumer products. While the prices of consumer products may change due to technological advancement, such as automation, which must be corrected for, salaries do not. If technological advancements are not accounted for within calculations based on consumer product prices, inflation can be confused with real wage changes, since both inflation and real wage changes affect the prices of consumer products. The method employed in this paper is a logical exercise. Logical arguments are presented that suggest the existence of many different feasible ways by which inflation can be determined. Then a short mathematical exercise will be presented which shows that one of these methods –using salaries – contains the fewest number of unknown parameters, and hence, is the preferred method, since the risk of mistakes is lower. From the results, it can be concluded that salaries, rather than consumer products, should be used to calculate inflation.
Abstract: One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).
Abstract: The cotton leafworm, Spodoptera littoralis (Boisduval) is a major insect pest of vegetables and cotton crops in Egypt, and exhibits different levels of tolerance to certain insecticides. Chlorantraniliprole has been registered recently in Egypt for control this insect. The susceptibilities of three S. littoralis populations collected from El Behaira governorate, north Egypt to chlorantraniliprole were determined by leaf-dipping technique on 4th instar larvae. Obvious variation of toxicity was observed among the laboratory susceptible, and three field populations with LC50 values ranged between 1.53 µg/ml and 6.22 µg/ml. However, all the three field populations were less susceptible to chlorantraniliprole than a laboratory susceptible population. The most tolerant populations were sampled from El Delengat (ED) Province where S. littoralis had been frequently challenged by insecticides. Certain enzyme activity assays were carried out to be correlated with the mechanism of the observed field population tolerance. All field populations showed significantly enhanced activities of detoxification enzymes compared with the susceptible strain. The regression analysis between chlorantraniliprole toxicities and enzyme activities revealed that the highest correlation is between α-esterase or β-esterase (α-β-EST) activity and collected field strains susceptibility, otherwise this correlation is not significant (P > 0.05). Synergism assays showed the ED and susceptible strains could be synergized by known detoxification inhibitors such as piperonyl butoxide (PBO), triphenyl phosphate (TPP) and diethyl-maleate (DEM) at different levels (1.01-8.76-fold and 1.09-2.94 fold, respectively), TPP showed the maximum synergism in both strains. The results show that there is a correlation between the enzyme activity and tolerance, and carboxylic-esterase (Car-EST) is likely the main detoxification mechanism responsible for tolerance of S. littoralis to chlorantraniliprole.
Abstract: This research studies the factors influencing the wages of native workers in Thailand's construction industry. The sample used comprised some 156 native construction workers from Songkhla Province, Thailand. The utilized research instrument was a questionnaire, with the data being analyzed according to frequency, percentage, and regression analysis. The results revealed that in general, native Thai construction workers are generally married males aged between 26 and 37 years old. They typically have four to six years of education, are employed as laborers with an average salary of 4,000–9,200 baht per month, and have fewer than five years of work experience. Most Thai workers work five days a week. Each establishment typically has 10–30 employees, with fewer than 10 of these being migrant workers in general. Most Thai workers are at a 20% to 40% risk from work, and they have never changed employer. The average wage of Thai workers was found to be 10,843.03 baht per month with a standard deviation of 4,898.31 baht per month. Hypothesis testing revealed that position, work experience, and the number of times they had switched employer were the factors most affecting the wages of native Thai construction workers. These three factors alone explain the salaries of Thai construction workers at 51.9%.
Abstract: This paper is to formulate a mathematical model to predict the amounts of the emissions produced from the combustion process of the gas turbine unit of the jet engine. These emissions have bad impacts on the environment if they are out of standards, which cause real threats to all type of life on the earth. The amounts of the emissions from the gas turbine engine are functions to many operational and design factors. In landing-takeoff (LTO) these amounts are not the same as in taxi or cruise of the plane using jet engines, because of the difference in the activity period during these operating modes. These emissions can be affected by several physical and chemical variables, such as fuel type, fuel to air ratio or equivalence ratio, flame temperature, combustion pressure, in addition to some inlet conditions such as ambient temperature and air humidity. To study the influence of these variables on the amounts of these emissions during the combustion process in the gas turbine unit, a computer program has been developed by using the visual basic 6 software. Here, the analysis of the combustion process is carried out by considering it as a chemical reaction with shifting equilibrium to find the products of the combustion of the octane fuel, at different equivalence ratios, compressor pressure ratios (CPR) and combustion temperatures. The results obtained have shown that there is noticeable influence of the equivalence ratio, CPR, and the combustion temperature on the amounts of the main emissions which are considered pollutants, such as CO, CO2 and NO.
Abstract: Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.
Abstract: The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.